This article first appeared in Forum, The Edge Malaysia Weekly on December 15, 2025 - December 21, 2025
Artificial intelligence (AI) is no longer a futuristic vision; it is actively reshaping industries worldwide. In Malaysia, the healthcare sector is undergoing a dramatic transformation, with AI’s market value projected to surge from US$10 million in 2022 to US$220 million by 2030, reflecting a compound annual growth rate of 45.42%. This rapid growth underscores AI’s potential to enhance diagnostic accuracy, streamline workflows and reduce operational costs. However, while healthcare broadly embraces AI, its integration into pharmacy practice remains comparatively gradual.
At its core, pharmacy practice is about ensuring that patients receive the right medication at the right dose and time, all while preventing medication-related errors. With increasing workloads, an ageing population and rising patient numbers, pharmacists are often stretched thin. AI offers a promising solution by automating administrative and repetitive tasks, thereby freeing pharmacists to focus on delivering quality patient care and enhancing medication management.
International studies provide compelling examples of AI’s impact on pharmacy practice. In France, a 2020 study of Lumio Medication, an AI-driven decision support system demonstrated improved precision and efficiency in detecting prescription errors. Over a two-week period, the system flagged 74% of prescriptions that required pharmacist intervention, with further assessments confirming that the remaining 26% of missed issues posed no critical risks.
Similarly, a Spanish study showcased a machine learning model that enabled community pharmacists to screen for early signs of mild cognitive impairment, successfully identifying potential cases in 17.4% of 728 participants. In the US, the AI-powered FindAir mobile app for asthma management tracks inhaler usage, detects improper techniques and offers real-time feedback, thereby extending pharmacists’ roles into remote patient monitoring.
AI has transformed fields like radiology, where deep learning algorithms detect abnormalities such as cancerous tumors with high accuracy. Similarly, AI-driven clinical decision support systems help physicians make evidence-based treatment decisions by analysing genomic and environmental data. In contrast, AI in pharmacy remains largely focused on workflow efficiency, underscoring the need for greater integration into patient-centred care.
In December 2024, Malaysia inaugurated a national AI office to shape policy and regulatory frameworks, aiming to become a regional AI development hub. The office will serve as a centralised agency for strategic planning, research and regulatory oversight in AI, with plans to deliver seven key initiatives in its first year, including an AI code of ethics, a regulatory framework and a five-year action plan until 2030.
The Malaysian government recognises AI’s potential in healthcare. Prime Minister Datuk Seri Anwar Ibrahim has emphasised that AI can boost efficiency and reduce cost wastage in the healthcare system. Studies suggest that AI could lower healthcare costs by 10% to 30%.
AI integration in pharmacy has the potential to transform medication prescribing, dispensing, administration and monitoring, addressing challenges such as increasing patient loads, complex regimens and limited healthcare resources in Malaysia’s hospitals. By analysing vast patient data and clinical guidelines, AI can recommend evidence-based drug treatments, optimise dosages and predict adverse reactions, enhancing both efficacy and safety.
The Ministry of Health is actively exploring AI’s role in healthcare, with a pilot project for AI-driven lung cancer detection underway at the National Cancer Institute and the Cyberjaya, Kajang and Putrajaya hospitals. Lung cancer, the leading cause of cancer-related deaths in Malaysia, is often diagnosed at late stages when treatment is costly and limited. AI-powered targeted screening could enable earlier detection, allowing for more effective and affordable treatment options.
AI also improves inventory management by analysing patient demographics, disease trends and prescription data to forecast drug demand. For instance, during flu season, AI-driven systems could predict surges in antiviral medication needs, ensuring better stock availability. Additionally, in hospital settings, AI enhances the safety and precision of parenteral nutrition and chemotherapy drug delivery by automating calculations, monitoring infusion rates and analysing patient responses to reduce human error.
Beyond hospitals, AI can drive efficiency and cost savings in the pharmaceutical industry, accelerating drug discovery by analysing large datasets to identify potential candidates and predict success rates before costly trials. Companies like Benevolent AI in London are already leveraging AI for faster drug development. Virtual trials and AI-driven simulations further refine drug formulations, reducing costs and time while making medications more affordable. McKinsey estimates that AI could generate US$60 billion (RM250 billion) to US$110 billion annually for pharmaceutical companies.
In a country where chronic diseases like diabetes and hypertension are prevalent, AI-powered adherence monitoring can support pharmacists in providing personalised interventions, improving medication compliance and, ultimately, enhancing long-term health outcomes.
Nonetheless, integrating AI into pharmacy practice presents several significant challenges. Many hospitals and clinics lack the critical infrastructure, such as electronic medical records, which are necessary for modern digital solutions. This shortfall is compounded by the disjointed nature of hospital and community pharmacy systems, which hinders seamless data sharing and complicates the integration of AI tools.
Moreover, the sector’s reliance on traditional methods for medication management, coupled with limited AI literacy among pharmacists, further impedes the transition to digital solutions. To overcome these skill gaps, it is essential to implement comprehensive training programmes and continuous professional development initiatives that equip pharmacists with the necessary technical expertise.
Additionally, AI systems in pharmacy must adhere to strict healthcare regulations to ensure patient safety and data security. This raises important questions of accountability. For instance, if an AI system issues an incorrect recommendation that results in patient harm, the question of responsibility remains unresolved. Clear governance guidelines, established by policymakers and healthcare regulators, are crucial to address these concerns and build trust in AI-driven solutions.
Furthermore, the cost of implementing AI technology can be prohibitive, particularly for smaller, independent community pharmacies. In this context, government incentives, subsidies or public-private partnerships could play a vital role in bridging the digital divide, ensuring that AI solutions are accessible across all sectors of the pharmacy industry.
For Malaysia to fully harness the benefits of AI in pharmacy practice, a collaborative approach is essential. Government agencies, pharmacy associations and technology developers must work together to overcome existing challenges. By investing in infrastructure, enhancing AI literacy among healthcare professionals and establishing clear regulatory guidelines, Malaysia can pave the way for a future where AI empowers pharmacists and elevates patient care.
The journey towards AI integration in Malaysian pharmacy practice may be fraught with obstacles, but the potential rewards are undeniable. By embracing AI, pharmacists can transition from traditional medication dispensers to pivotal players in personalised, data-driven healthcare. The future of pharmacy is bright, and it is time for Malaysia to embrace this new era with open arms.
David Chang is a research officer at BranX-ON Marketing. Lorraine Hoo is a pharmacist.
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